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fpylll ships with Sage 7.4. Thus, it is available via SageMathCell and SageMathCloud (select a Jupyter notebook with a Sage 7.4 kernel, the default Sage worksheet still runs Sage 7.3 at the time of writing). You can also fire up a dply.co virtual server with the latest fpylll/fplll preinstalled (it takes perhaps 15 minutes until everything is compiled).

Getting Started

Note: fpylll is also available via PyPI and Conda-Forge for Conda. In what follows, we explain manual installation.

Install the required libraries - GMP or MPIR and MPFR - if not available already. You may also want to install QD.

Install fplll:

$ (fpylll) ./install-dependencies.sh $VIRTUAL_ENV

Some OSX users report that they required export CXXFLAGS="-stdlib=lic++ -mmacosx-version-min=10.7 and export CXX=clang++ (after installing a recent clang with brew) since the default GCC installed by Apple does not have full C++11 support.

Multicore Support

fpylll supports parallelisation on multiple cores. For all C++ support to drop the GIL is enabled, allowing the use of threads to parallelise. Fplll is thread safe as long as each thread works on a separate object such as IntegerMatrix or MatGSO. Also, fpylll does not actually drop the GIL in all calls to C++ functions yet. In many scenarios using multiprocessing, which sidesteps the GIL and thread safety issues by using processes instead of threads, will be the better choice.

The example below calls LLL.reduction on 128 matrices of dimension 30 on four worker processes.

To test threading simply replace the line from multiprocessing import Pool with from multiprocessing.pool import ThreadPool as Pool. For calling BKZ.reduction this way, which expects a second parameter with options, using functools.partial is a good choice.

Contributing

fpylll welcomes contributions, cf. the list of open issues. To contribute, clone this repository, commit your code on a separate branch and send a pull request. Please write tests for your code. You can run them by calling:

$ (fpylll) py.test

from the top-level directory which runs all tests in tests/test_*.py. We run flake8 on every commit automatically, In particular, we run: